Emission factors of volatile organic compounds (VOCs) based on the detailed vehicle classification in a tunnel study

Zhang, Qi‐Jun; Wu, Lin; Fang, Xiaozhen; Liu, Mingyue; Zhang, Jing; Shao, Min; Lü, Sihua; Mao, Hongjun

doi:10.1016/j.scitotenv.2017.12.171

Cited by 86 publications

(43 citation statements)

References 27 publications

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“…Meteorological data including temperature (T), relative humidity (RH), wind speed (WS), wind direction (WD), and atmospheric pressure (P) were measured using VAISALA WXT520 (Helsinki, Finland) automatic weather stations with a time resolution of 1 min. The actual volumetric flow rates induced by the vehicular fleet and the prevailing winds in the tunnel were continuously measured using ultrasonic gas flowmeters (Flowsick-200 SICK MAIHAK, Germany) with a time resolution of 1 min, which have also been used in previous tunnel tests (Song et al, 2018;Zhang et al, 2018b;Imhof et al, 2006).…”

Section: Measurements and Analytic Methodsmentioning

confidence: 99%

“…A total of 99 target NMVOC species (29 alkanes,12 alkenes,16 aromatics,28 Halocarbons,and 14 OVOCs (oxygenated VOCs)) were analyzed using a high-resolution gas chromatography-flame ionization detector (GC-FID) and gas chromatography-mass selective detector (GC-MS). Details regarding the laboratory analysis of the NMVOCs can be found in our previous study (Zhang et al, 2018b).…”

Section: Measurements and Analytic Methodsmentioning

confidence: 99%

“…The average EFs for vehicles traveling through the tunnel were estimated using the following formula which has been widely used in previous studies (Song et al, 2018;Fang et al, 2018;Zhang et al, 2018b;Gertler et al, 1996;Pierson et al, 1996;Pierson and Brachaczek, 1983).…”

Section: Emission Factor Calculationmentioning

confidence: 99%

“…The maximum incremental reactivity (MIR) factors from Carter (1994) were used to calculate the OFP from vehicle emissions. The MIR factors are in units of grams of O 3 per gram of NMVOCs; therefore, the EF of potential O 3 for individual NMVOC could be estimated by the MIR coefficient times the EF for each NMVOC species (Zhang et al, 2018b;Cui et al, 2018;Ho et al, 2009).…”

Section: Ozone Formation Potentialmentioning

confidence: 99%

“…Our results are comparable to those from Dallmann et al (2013)'s study, which reported that the EFs of organic aerosol and black carbon from heavy-duty diesel trucks were 10 and 50 times higher than those of LDV in the United States in 2010, respectively. However, because of the insignificant variation in the compositions of the vehicular emission standards (from China I to China V) during the measurement campaign ( Fig.A3c), an attempt to differentiate EFs under different emission standards by multiple linear regression (Zhang et al, 2018b;Hwa et al, 2002) failed. Although the EFs estimated by the tunnel tests were considered as EFs in a real-world setting, there were still several limitations, such as the limited speeds and accelerations, and that most of the vehicles were operating under hot-stabilized conditions (Gertler, 2005).…”

Section: Emission Factors Of No-no 2 -No X and Comentioning

confidence: 99%

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Vehicular volatile organic compounds (VOCs)-NOx-CO emissions in a tunnel study in northern China: emission factors, profiles, and source apportionment

Song

Liu

Sun

et al. 2018

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Abstract. Vehicular emission is a key contributor to ambient volatile organic compounds (VOCs) and NOx in Chinese megacities. However, the information of real-world emission factors (EFs) for a typical urban fleet is still limited, hindering the development of a more reliable emission inventory in China. Based on a more-than-two-week (August 8&ndash;24, 2017) tunnel test in urban Tianjin in northern China, and on the use of a statistical regression model, the Positive Matrix Factorization (PMF) receptor model, and the Calculate Emissions from Road Transport (COPERT) IV model, characteristics of vehicular VOCs-NOx-CO emissions were analyzed systematically. The fleet-average EFs (pollutant: downslope, upslope, and overall in mgkm&minus;1veh&minus;1) were estimated respectively as follows: (NO: 61.92±72.46, 158.58±73.48, 97.52±69.84), (NO2: 16.52±11.49, 23.98±20.14, 15.86±9.38), (NOx: 79.45±78.43, 181.22±88.29, 116.56±77.61), and (CO: 269.96±342.38, 577.76±382.22, 344.67±250.01). The EFs of NO-NO2-NOx and CO from heavy-duty vehicles (or diesel vehicles) were differentiated from light-duty vehicles (or gasoline vehicles). The ratios (v/v) of NO2 to NOx in the primary vehicular exhaust were approximately 0.18±0.09, 0.10±0.22 and 0.10±0.05 for downslope, upslope, and the entire tunnel, respectively. The fleet-average EF of the 99-target non-methane VOCs (NMVOCs) was 40.56±12.18mgkm&minus;1veh&minus;1, lower than the previous studies in China. The BTEX (benzene, toluene, ethylbenzene, p-xylene, m-xylene and o-xylene) levels decreased by approximately 79% when emission standards increased from China I to China V. The source profiles of NMVOCs from the tailpipe and evaporative emissions were resolved by the PMF model. The evaporative emissions accounted for nearly one-half of the total vehicular VOC emissions, indicating that evaporative and tailpipe emissions contributed equally to VOC emissions. The relative contributions of evaporative NMVOC emissions to total vehicular NMVOC emissions are temperature-dependent with the average increasing ratio of 7.55%&deg;C&minus;1. The primary emission ratio (ER, m/m) of VOCs/NOx was approximately 2.04, suggesting that vehicular NOx and VOCs can be co-emitted with a proper ER. According to the vehicular ERs of VOCs/NOx in Tianjin (2000&ndash;2016) and China (2010&ndash;2030), as even more stringent emission standards are implemented in the future, the O3 chemical regimes were likely to be VOCs-limited (i.e., 8:1 threshold) for cities or regions where VOCs and NOx emissions are dominated by vehicular exhaust. Our study enriched the database on the fleet-average emission factors of on-road vehicles for emission inventory, air quality modeling, and health effects studies, provided implications for following O3 control in China from the view of primary emission, and highlighted the importance of further control of evaporative emissions.

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Section: Measurements and Analytic Methodsmentioning

confidence: 99%

Section: Measurements and Analytic Methodsmentioning

confidence: 99%

Section: Emission Factor Calculationmentioning

confidence: 99%

Section: Ozone Formation Potentialmentioning

confidence: 99%

Section: Emission Factors Of No-no 2 -No X and Comentioning

confidence: 99%

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Vehicular volatile organic compounds (VOCs)-NOx-CO emissions in a tunnel study in northern China: emission factors, profiles, and source apportionment

Song

Liu

Sun

et al. 2018

Preprint

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Characteristics and Source Apportionment of Volatile Organic Compounds in a Coastal Industrial Area: A Case Study in the Yangtze River Delta of China

Chen,

Ling,

Liu

et al. 2024

Bull Environ Contam Toxicol

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Profiles and Source Apportionment of Nonmethane Volatile Organic Compounds in Winter and Summer in Xi’an, China, based on the Hybrid Environmental Receptor Model

et al. 2020

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Emission factors of volatile organic compounds (VOCs) based on the detailed vehicle classification in a tunnel study

Cited by 86 publications

References 27 publications

Vehicular volatile organic compounds (VOCs)-NO<sub><i>x</i></sub>-CO emissions in a tunnel study in northern China: emission factors, profiles, and source apportionment

Vehicular volatile organic compounds (VOCs)-NO<sub><i>x</i></sub>-CO emissions in a tunnel study in northern China: emission factors, profiles, and source apportionment

Characteristics and Source Apportionment of Volatile Organic Compounds in a Coastal Industrial Area: A Case Study in the Yangtze River Delta of China

Profiles and Source Apportionment of Nonmethane Volatile Organic Compounds in Winter and Summer in Xi’an, China, based on the Hybrid Environmental Receptor Model

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Emission factors of volatile organic compounds (VOCs) based on the detailed vehicle classification in a tunnel study

Cited by 86 publications

References 27 publications

Vehicular volatile organic compounds (VOCs)-NO&lt;sub&gt;&lt;i&gt;x&lt;/i&gt;&lt;/sub&gt;-CO emissions in a tunnel study in northern China: emission factors, profiles, and source apportionment

Vehicular volatile organic compounds (VOCs)-NO&lt;sub&gt;&lt;i&gt;x&lt;/i&gt;&lt;/sub&gt;-CO emissions in a tunnel study in northern China: emission factors, profiles, and source apportionment

Characteristics and Source Apportionment of Volatile Organic Compounds in a Coastal Industrial Area: A Case Study in the Yangtze River Delta of China

Profiles and Source Apportionment of Nonmethane Volatile Organic Compounds in Winter and Summer in Xi’an, China, based on the Hybrid Environmental Receptor Model

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Vehicular volatile organic compounds (VOCs)-NO<sub><i>x</i></sub>-CO emissions in a tunnel study in northern China: emission factors, profiles, and source apportionment

Vehicular volatile organic compounds (VOCs)-NO<sub><i>x</i></sub>-CO emissions in a tunnel study in northern China: emission factors, profiles, and source apportionment